107 citations · 160 across the 9 of their papers we have counts for
14 papers
Bayesian fusion forests for heterogeneous treatment effects on survival from randomised and real-world data
Tijn Jacobs, Stéphanie L. van der Pas, Wessel N. van Wieringen
We develop the Bayesian fusion forest, a nonparametric framework to estimate heterogeneous treatment effects on survival outcomes by combining a randomised controlled trial and rea…
Horseshoe Forests for High-Dimensional Causal Survival Analysis
Tijn Jacobs, Wessel N. van Wieringen, Stéphanie L. van der Pas
We develop a Bayesian tree ensemble model to estimate heterogeneous treatment effects in censored survival data with high-dimensional covariates. Instead of imposing sparsity throu…
A Flexible Model for Record Linkage
Kayané Robach, Stéphanie L van der Pas, Mark A van de Wiel +1
Combining data from various sources empowers researchers to explore innovative questions, for example those raised by conducting healthcare monitoring studies. However, the lack of…
Bayesian regression discontinuity design with unknown cutoff
Julia Kowalska, Mark van de Wiel, Stéphanie van der Pas
The regression discontinuity design (RDD) is a quasi-experimental approach used to estimate the causal effects of an intervention assigned based on a cutoff criterion. RDD exploits…
Bayesian sensitivity analysis for a missing data model
Bart Eggen, Stéphanie L. van der Pas, Aad W. van der Vaart
In causal inference, sensitivity analysis is important to assess the robustness of study conclusions to key assumptions. We perform sensitivity analysis of the assumption that miss…
Asymptotics of Caliper Matching Estimators for Average Treatment Effects
Máté Kormos, Stéphanie van der Pas, Aad van der Vaart
Caliper matching is used to estimate causal effects of a binary treatment from observational data by comparing matched treated and control units. Units are matched when their prope…
CGR-CUSUM: A Continuous time Generalized Rapid Response Cumulative Sum chart
Daniel Gomon, Hein Putter, Rob G. H. H. Nelissen +1
Rapidly detecting problems in the quality of care is of utmost importance for the well-being of patients. Without proper inspection schemes, such problems can go undetected for yea…
Multiscale Bayesian Survival Analysis
Ismaël Castillo, Stéphanie van der Pas
We consider Bayesian nonparametric inference in the right-censoring survival model, where modeling is made at the level of the hazard rate. We derive posterior limiting distributio…
Posterior Concentration for Bayesian Regression Trees and Forests
Veronika Rockova, Stephanie van der Pas
Since their inception in the 1980's, regression trees have been one of the more widely used non-parametric prediction methods. Tree-structured methods yield a histogram reconstruct…
Bayesian Community Detection
Stéphanie van der Pas, Aad van der Vaart
We introduce a Bayesian estimator of the underlying class structure in the stochastic block model, when the number of classes is known. The estimator is the posterior mode correspo…
Uncertainty quantification for the horseshoe
Stéphanie van der Pas, Botond Szabó, Aad van der Vaart
We investigate the credible sets and marginal credible intervals resulting from the horseshoe prior in the sparse multivariate normal means model. We do so in an adaptive setting w…
Conditions for Posterior Contraction in the Sparse Normal Means Problem
Stéphanie van der Pas, Jean-Bernard Salomond, Johannes Schmidt-Hieber
The first Bayesian results for the sparse normal means problem were proven for spike-and-slab priors. However, these priors are less convenient from a computational point of view.…
Almost the Best of Three Worlds: Risk, Consistency and Optional Stopping for the Switch Criterion in Nested Model Selection
Stéphanie van der Pas, Peter Grünwald
We study the switch distribution, introduced by Van Erven et al. (2012), applied to model selection and subsequent estimation. While switching was known to be strongly consistent,…
The Horseshoe Estimator: Posterior Concentration around Nearly Black Vectors
S. L. van der Pas, B. J. K. Kleijn, A. W. van der Vaart
We consider the horseshoe estimator due to Carvalho, Polson and Scott (2010) for the multivariate normal mean model in the situation that the mean vector is sparse in the nearly bl…